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Serverless Scaling for Ingesting, Aggregating, and Visualizing Apache Logs with Amazon Kinesis Firehose, AWS Lambda, and Amazon Elasticsearch Service | AWS Database Blog

In 2016, AWS introduced the EKK stack (Amazon Elasticsearch Service, Amazon Kinesis, and Kibana, an open source plugin from Elastic) as an alternative to ELK (Amazon Elasticsearch Service, the open source tool Logstash, and Kibana) for ingesting and visualizing Apache logs. One of the main features of the EKK stack is that the data transformation is handled via the Amazon Kinesis Firehose agent. In this pos ...

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Manage Query Workloads with Query Monitoring Rules in Amazon Redshift | AWS Big Data Blog

Data warehousing workloads are known for high variability due to seasonality, potentially expensive exploratory queries, and the varying skill levels of SQL developers. To obtain high performance in the face of highly variable workloads, Amazon Redshift workload management (WLM) enables you to flexibly manage priorities and resource usage. With WLM, short, fast-running queries don’t get stuck in queues behi ...

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Send Apache Web Logs to Amazon Elasticsearch Service with Kinesis Firehose | AWS Database Blog

We have many customers who own and operate Elasticsearch, Logstash, and Kibana (ELK) stacks to load and visualize Apache web logs, among other log types. Amazon Elasticsearch Service provides Elasticsearch and Kibana in the AWS Cloud in a way that’s easy to set up and operate. Amazon Kinesis Firehose provides reliable, serverless delivery of Apache web logs (or other log data) to Amazon Elasticsearch Servic ...

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Implement Serverless Log Analytics Using Amazon Kinesis Analytics | AWS Big Data Blog

Applications log a large amount of data that—when analyzed in real time—provides significant insight into your applications. Real-time log analysis can be used to ensure security compliance, troubleshoot operation events, identify application usage patterns, and much more. Ingesting and analyzing this data in real time can be accomplished by using a variety of open source tools on Amazon EC2. Alternatively, ...

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Powering Amazon Redshift Analytics with Apache Spark and Amazon Machine Learning | AWS Big Data Blog

Air travel can be stressful due to the many factors that are simply out of airline passengers’ control. As passengers, we want to minimize this stress as much as we can. We can do this by using past data to make predictions about how likely a flight will be delayed based on the time of day or the airline carrier. In this post, we generate a predictive model for flight delays that can be used to help us pick ...

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This company is using Amazon Snowmobile to transfer petabytes of data to the cloud

One of the most dramatic announcements from Amazon Web Services at its 2016 re:Invent conference was the announcement of Snowmobile: It’s a 45’ semi truck that trailers a data center on wheels. Customers can load it up with up to 100 petabytes of data per Snowmobile, which is then driven to an AWS data center and loaded into the company’s cloud. It begs the question: Who’s actually using this? DigitalGlobe ...

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Data Wrangling at Slack

For a company like Slack that strives to be as data-driven as possible, understanding how our users use our product is essential. The Data Engineering team at Slack works to provide an ecosystem to help people in the company quickly and easily answer questions about usage, so they can make better and data informed decisions: “Based on a team’s activity within its first week, what is the probability that it ...

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Low-Latency Access on Trillions of Records: FINRA’s Architecture Using Apache HBase on Amazon EMR with Amazon S3 | AWS Big Data Blog

The Financial Industry Regulatory Authority (FINRA) is a private sector regulator responsible for analyzing 99% of the equities and 65% of the option activity in the US. In order to look for fraud, market manipulation, insider trading, and abuse, FINRA’s technology group has developed a robust set of big data tools in the AWS Cloud to support these activities. One particular application, which requires low- ...

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Apache Impala (incubating) vs. Amazon Redshift: S3 Integration, Elasticity, Agility, and Cost-Performance Benefits on AWS – Cloudera Engineering Blog

As measured across multiple dimensions (see analysis below), Impala provides a better cloud-native experience than Redshift for a number of common use cases. Impala 2.6 brings read/write support on Amazon S3, which provides cloud capabilities such as direct querying of data from S3, elastic scaling of compute, and seamless data portability and flexibility that are unique amongst cloud-based analytic databas ...

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Encrypt Data At-Rest and In-Flight on Amazon EMR with Security Configurations

Customers running analytics, stream processing, machine learning, and ETL workloads on personally identifiable information, health information, and financial data have strict requirements for encryption of data at-rest and in-transit. The Apache Spark and Hadoop ecosystems lend themselves to these big data use cases, and customers have asked us to provide a quick and easy way to encrypt data at-rest and dat ...

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